Multi-UAV Path Planning for Air-Ground Relay Communication Based on Mix-Greedy MAPPO Algorithm by Yiquan Wang, Yan Cui, Yu Yang, Zhaodong Li, Xing Cui

“…In this paper, a Multi-Agent Reinforcement Learning (MARL) method based on the ε-greedy strategy and multi-agent proximal policy optimization (MAPPO) algorithm is proposed to address the local optimization problem, improving the communication efficiency and task execution capability of UAV cluster control. …”
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Determinate arbitrary quantum state engineering through one-dimensional quantum walks by Yu Wang, Meng Li, Yuan-Yuan Zhao

“…This efficient method for preparing quantum superposition states lays a foundation for advancing quantum technologies, with broad applications in quantum information processing.…”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To address these limitations, this study employs the covariance matrix decomposition method to generate 3D lognormal random fields for soil parameters, enabling efficient modeling of spatial variability. …”
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Robust Traffic Signal Retiming Based on Queue Service Time Estimation Using Low-Penetration Connected Vehicle Data by Chengchuan An, Weihua Zhang, Yinpu Wang, Siping Ke, Jingxin Xia

“…However, the existing methods are mostly deterministic and do not well consider the uncertainty in both traffic demand and capacity. …”
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Chance-Constrained Optimization of Photovoltaic System Allocation considering Power Loss, Voltage Level, and Line Current by Ibrahim Cagri Barutcu

“…This present study focuses on investigating impact of uncertainties in PV system operating under different irradiance scenarios on power loss with probabilistic constraints in distribution networks instead of precise deterministic limits to contribute more efficient and reliable use of energy. …”
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Leading Degree: A Metric for Model Performance Evaluation and Hyperparameter Tuning in Deep Learning-Based Side-Channel Analysis by Junfan Zhu, Jiqiang Lu

“…To attain an effective generic side-channel evaluation metric, we investigate the deterministic component of power consumption, find that the elements of score vector under a key follow a linearly transformed chi-square distribution approximately, and some wrong key hypotheses usually with top scores provide great assistance in model performance evaluation, and finally we propose a new metric called Leading Degree (LD) as well as its simplified version LD-simplified for measuring model performance, which offers similar accuracy but much better generality and efficiency compared with the classical side-channel benchmark metric TGE1, and offers similar generality and efficiency but significantly better accuracy compared with recently proposed sidechannel metrics like Label Correlation and Cross Entropy Ratio. …”
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LIGHTWEIGHT DESIGN FOR OVERHAUL TOOLING SUPPORT SEAT BASED ON TOPOLOGY OPTIMIZATION AND SIX SIGMA ROBUSTNESS by WANG ZiNing, WU JianJun, XIANG JianMing, WANG BaiSong, JIN YingQi

“…The results show that reliability of the design variables,strength and stiffness are all 1,reaching eight sigma level,the support seat’s weight is reduced by 67. 0% and the lightweight effect is remarkable; compared with the support seat’s traditional deterministic optimization design after topology optimization,this method enhances the strength and stiffness of the support seat,meanwhile,improves the reliability of the optimization design,the robustness of the strength,the robustness of the stiffness and the consistency of the weight. …”
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Insurance: is it better together? by E. A. Rusetskaya, D. A. Zakharova, A. A. Krechetova, A. I. Shchetinskaya, Ya. D. Gundar, K. S. Frolov

“…The study intends to identify the potential reasons for the relatively insignificant share of MIS in the insurance market and to assess the attractiveness of the latter in increasing the efficiency of the insurance mechanism in the system of ensuring the financial security of citizens and economic entities.Materials and methods. …”
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Quantum-inspired robust optimization for coordinated scheduling of PV-hydrogen microgrids under multi-dimensional uncertainties by Yunxiao Bai, Yu Sui, Xiaoyu Deng, Xiangbing Wang

“…These include fluctuations in PV output, stochastic hydrogen demand, and volatile market prices. Traditional deterministic or static robust methods often fall short in handling such dynamic, multi-dimensional uncertainties. …”
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Modeling and Forecasting Electricity Demand and Prices: A Comparison of Alternative Approaches by Ismail Shah, Hasnain Iftikhar, Sajid Ali

“…The estimation of these models is carried out by four different estimation methods, including ordinary least squares (O), Lasso (L), Ridge (R), and Elastic-net (E). …”
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Effect of Warming on Soil Fungal Community Along Altitude Gradients in a Subalpine Meadow by Jing Yin, Dandan Yuan, Jing Lu, He Li, Shuzheng Luo, Jianhua Zhang, Xingjia Xiang

“…This study aimed to evaluate the effects of warming on aboveground grass, belowground soil properties, and fungal community along altitude gradients in the subalpine meadow of Mount Wutai using the high-throughput sequencing method. Warming reduced the restriction of low temperatures on the growth of subalpine grass, resulting in increasing grass biomass, community height, and coverage. …”
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Probabilistic-Aware Satellite Constellation Scheduling for Integrated TN-NTN Operations by Arnau Singla, Isabel Gallardo-Duval, Anna Calveras, Juan A. Fraire, Joan A. Ruiz-De-Azua

“…By leveraging statistical traffic models based on the central limit theorem, the proposed method accounts for traffic uncertainty and embeds it directly into the scheduling process. …”
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Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation by Zhi Li, Dawei Xie, Haifeng Ye, Yujun Li, Jinzhong Li, Yichi Chen, Yue Yang

“…Furthermore, these constraints are transformed into their deterministic equivalents using quantile-based methods. …”
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Gaslike Social Motility: Optimization Algorithm with Application in Image Thresholding Segmentation by Oscar D. Sanchez, Luz M. Reyes, Arturo Valdivia-González, Alma Y. Alanis, Eduardo Rangel-Heras

“…Additionally, GSM’s efficiency in image thresholding segmentation is highlighted, as it achieves high-quality results with fewer iterations and particles compared to other methods.…”
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Coordinated Reentry Guidance with A* and Deep Reinforcement Learning for Hypersonic Morphing Vehicles Under Multiple No-Fly Zones by Cunyu Bao, Xingchen Li, Weile Xu, Guojian Tang, Wen Yao

“…The A* algorithm generates heuristic trajectories circumventing no-fly zones, reducing the evaluation function by 6.2% compared to greedy methods, while DDPG optimizes sweep angles to minimize velocity loss and terminal errors (0.09 km position, 0.01 m/s velocity). …”
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Energy Management in Microgrids Using Model-Free Deep Reinforcement Learning Approach by Odia A. Talab, Isa Avci

“…MGs offer a flexible and efficient framework for accommodating dispersed energy resources. …”
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Pharmacoeconomic study of various treatment options for superficial vein thrombophlebitis of lower extremities by R. E. Kalinin, I. A. Suchkov, M. M. Uporov, D. S. Titov, M. Yu. Klishchenko

“…Objective: рharmacoeconomic evaluation of pharmacotherapy, crossectomy (in combination with pharmacotherapy) and phlebectomy (in combination with pharmacotherapy) in patients with SVT of lower extremities.  Material and methods. Pharmacoeconomic evaluation was carried out using cost-effectiveness analysis (CEA) by calculating the costeffectiveness ratio (CER). …”
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Optimal Control and Cost-Effectiveness Analysis of Cholera with Vaccination by Fikru Shiferaw Tessema, Purnachandra Rao Koya, Boka Kumsa Bole

“…The simulation study has revealed that the application of prevention methods will play a significant role in controlling or minimizing the spread of the disease. …”
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Two-stage multi-timescale optimal scheduling for electricity-hydrogen coupling systems based on scenario approach and deep reinforcement learning by CHEN Zhe, WEI Meijia, LIN Da, LI Zhihao, CHEN Jian

“…The short-term model focuses on minimizing the systems’ operational costs and is solved using the deep deterministic policy gradient （DDPG） algorithm. Finally， case study simulations demonstrate that the proposed method effectively facilitates hydrogen energy shifting， smooths fluctuations in wind and solar output， verifying the method’s effectiveness.…”
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Artificial Intelligence in UAV Flight Controls: Deep Reinforcement Learning Based Altitude-Hold Strategies for Fixed-Wing UAVs by Hasan Raza Khanzada, Adnan Maqsood, Abdul Basit

“…The deep deterministic policy gradient (DDPG) method was chosen to suit environments with continuous action spaces. …”
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